Papers
A Theoretical Analysis of Detecting Large Model-Generated Time Series
Junji Hou, Junzhou Zhao, Shuo Zhang et al.
Gradient-Protected Value Decomposition for Cooperative Multi-Agent Reinforcement Learning
Jie Hou, Haowen Dou, Lujuan Dang et al.
Harmonic Dataset Distillation for Time Series Forecasting
Seungha Hong, Sanghwan Jang, Wonbin Kweon et al.
Lost in Time? A Meta-Learning Framework for Time-Shift-Tolerant Physiological Signal Transformation
Qian Hong, Cheng Bian, Xiao Zhou et al.
HINPool: A Unified Heterogeneous Graph Pooling Framework for Accurate Molecular and Protein Property Prediction
Ming-Yi Hong, You-Chen Teng, Shao-En Lin et al.
Distributional Priors Guided Diffusion for Generating 3D Molecules in Low Data Regimes
Haokai Hong, Wanyu Lin, Ming Yang et al.
From Attribution to Action: Jointly ALIGNing Predictions and Explanations
Dongsheng Hong, Chao Chen, Yanhui Chen et al.
Uncertainty Quantification for Machine Learning: One Size Does Not Fit All
Paul Hofman, Yusuf Sale, Eyke Hüllermeier
Beyond Fixed Depth: Adaptive Graph Neural Networks for Node Classification Under Varying Homophily
Asela Hevapathige, Asiri Wijesinghe, Ahad N. Zehmakan
Posterior Label Smoothing for Node Classification
Jaeseung Heo, MoonJeong Park, Dongwoo Kim
Out-of-Distribution Detection with Positive and Negative Prompt Supervision Using Large Language Models
Zhixia He, Chen Zhao, Minglai Shao et al.
Harnessing Vision-Language Models for Time Series Anomaly Detection
Zelin He, Sarah Alnegheimish, Matthew Reimherr
Deferred Poisoning: Making the Model More Vulnerable via Hessian Singularization
Yuhao He, Jinyu Tian, Xianwei Zheng et al.
Dual Mamba for Node-Specific Representation Learning: Tackling Over-Smoothing with Selective State Space Modeling
Xin He, Yili Wang, Yiwei Dai et al.
A Stage-Aware Mixture of Experts Framework for Neurodegenerative Disease Progression Modelling
Tiantian He, Keyue Jiang, An Zhao et al.
Reliability-Guaranteed and Reward-Seeking Sequence Modeling for Model-Based Offline Reinforcement Learning
Shenghong He, Chao Yu, Qian Lin et al.
Harnessing Textual Semantic Priors for Knowledge Transfer and Refinement in CLIP-Driven Continual Learning
Lingfeng He, De Cheng, Di Xu et al.
Improving Generalization in Offline Meta-Reinforcement Learning via Cross-task Contexts
Hongcai He, Zetao Zheng, Anjie Zhu et al.
HiQ-Lip: A Hierarchical Quantum-Classical Method for Global Lipschitz Constant Estimation of ReLU Networks
Haoqi He, Yan Xiao, Wenzhi Xu et al.
Towards Federated Clustering: A Client-wise Private Graph Aggregation Framework
Guanxiong He, Zheng Wang, Jie Wang et al.
S2-Boost: Synergistic Semantic Boosting for Coarse-to-Fine Ensemble Learning
Guanxiong He, Zheng Wang, Jie Wang et al.
Forgetting by Pruning: Data Deletion in Join Cardinality Estimation
Chaowei He, Yuanjun Liu, Qingzhi Ma et al.
Aggregate-Combine-Readout GNNs Can Express Logical Classifiers Beyond the Logic C2
Stan P Hauke, Przemysław Andrzej Wałęga
Federated Graph-level Clustering Network with Attribute Inference
Renda Han, Junlong Wu, Wenxuan Tu et al.
Oligodendrocyte-Driven Spiking Neural Model
Mengqiao Han, Liyuan Pan, Xiabi Liu et al.